Supondo-se que os robôs coexistirão conosco num futuro próximo, é então evidente a necessidade de Arquiteturas de Controle Inteligentes voltadas para a Interação Humano-Robô. Portanto, este trabalho desenvolveu uma Organização de Arquitetura de Controle Inteligente comportamental, cujo objetivo principal é permitir que o robô interaja com as pessoas de maneira intuitiva e que motive a colaboração entre pessoas e robôs. Para isso, um módulo emocional sintético, embasado na teoria bidimensional de emoções, foi integrado para promover a adaptação dos comportamentos do robô, implementados por Esquemas Motores, e a comunicação de seu estado interno de modo inteligível. Esta Organização subsidiou a implantação da Arquitetura de Controle em uma aplicação voltada para a área assistencial da saúde, consistindo, destarte, em um estudo de caso em robótica social assistiva como ferramenta auxiliar para educação especial. Os experimentos realizados demonstraram que a arquitetura de controle desenvolvida é capaz de atender aos requisitos da aplicação, conforme estipulado pelos especialistas consultados. Isto posto, esta tese contribui com o projeto de uma arquitetura de controle capaz de agir mediante a avaliação subjetiva baseada em crenças cognitivas das emoções, o desenvolvimento de um robô móvel de baixo-custo, e a elaboração do estudo de caso em educação especial. / Assuming that robots will coexist with humans in the near future, it is conspicuous the need of Intelligent Control Architectures suitable for Human-Robot Interaction. Henceforth, this research has developed a behavioral Control Architecture Organization, whose main purpose is to allow the intuitive interaction of robot and people, thus fostering the collaboration between them. To this end, a synthetic emotional module, based on the Circumplex emotion theory, promoted the adaptation of the robot behaviors, implemented using Motor Schema theory, and the communication of its internal state. This Organization supported the adoption of the Control Architecture into an assistive application, which consists of the case study of assistive social robots as an auxiliary tool for special education. The experiments have demonstrated that the developed control architecture was able to meet the requirements of the application, which were conceived according to the opinion of the consulted experts. Thereafter, this thesis contributes with the design of a control architecture that is able to act upon the subjective evaluation based on cognitive beliefs of emotions, the development of a low-cost mobile robot, and the development of the case study in special education.

Este trabalho de pesquisa objetivou a obtenção de uma nova política de operação que melhor caracterizasse o comportamento ótimo dos sistemas hidrelétricos de potência, mesmo diante das mais variadas condições hidrológicas. Este trabalho teve duas linhas de investigação. Uma tratou do problema de previsão de vazões afluentes mensais, na busca por abordagens e técnicas que definissem bons modelos de previsão. A outra linha de pesquisa tratou de encontrar uma nova política de operação, para o problema de planejamento da operação, que fosse capaz de definir uma seqüência de decisões operativas mais estáveis, confiáveis e de menor custo operativo. Na primeira linha de pesquisa, investigou-se três aspectos importantes na definição de um modelo de previsão: técnicas de pré-processamento dos dados, definição automática do espaço de entrada e avaliação do desempenho de alguns modelos de redes neurais e sistemas Fuzzy como modelos de previsão. Nestes aspectos foram investigadas a utilização da análise dos componentes principais e o tratamento da série temporal de vazões afluentes como um sinal discreto, utilizando-se a representação \"analytic signal\". Para a definição do espaço de entrada de maneira automática utilizou-se a abordagem da \"dynamic modelling\", empregando-se a \"average mutual information\" e \"false nearest neighbors\". Para implementação dos modelos de previsão foram estudados e avaliados quatro modelos inteligentes: rede SONARX, rede SONARX-RBF, modelo ANFIS e a rede ESN. Já na outra linha de pesquisa, foi proposta uma política de operação que fosse capaz de estabilizar os despachos de geração termelétrica e conseqüentemente o custo marginal de operação. A política de operação preditiva estabilizada via termo inercial produziu excelentes resultados operativos, melhorando de forma significativa a performance da política preditiva. / This research work aimed at obtaining a new operation policy which could better describe the optimal behavior of hydropower systems, even when faced with the most varied hydrological conditions. This research had two lines of investigation. The first one dealt with the monthly water inflow forecasting problem, searching for approaches and techniques which could define efficient forecasting models. Three important aspects to define a forecasting model were investigated: data pre-processing techniques, automatic definition of the embedding and the performance assessment of some artificial neural networks and Fuzzy systems. Hence, the use of the principal components analysis was investigated and, considering the water inflow time series as a discrete signal, the analytic signal representation could be used to preprocess the data. Furthermore, the embedding was automatically defined using the dynamic modelling approach, by using the average mutual information and the false nearest neighbors techniques. The forecasting models were implemented by four intelligent models: SONARX network, SONARX-RBF network, ANFIS model and the ESN network. The other line of investigation came up with a new operation policy to solve the operation planning problem, defining a more stable, reliable and less costly operative decision sequence. It was proposed an approach to stabilize the thermoelectric generation dispatches and, as a result, the operative marginal cost. The predictive operation policy stabilized via inertial term produced excellent operation results, improving the performance of the predictive policy.

É importante que as redes elétricas tenham altos índices de confiabilidade, de forma a se manter a agilidade e a manutenção ideais para um melhor funcionamento. Por outro lado, o crescimento inesperado da carga, falhas em equipamentos e uma parametrização inadequada das funções de proteção tornam a análise de eventos de proteção mais complexas e demoradas. Além disso, a quantidade de informações que pode ser obtida de relés digitais modernos tem crescido constantemente. Para que seja possível uma rápida tomada de decisão e manutenção, esse projeto de pesquisa teve como objetivo a implementação de um sistema completo de diagnóstico que é ativado automaticamente quando um evento de proteção ocorrer. As informações a serem analisadas são obtidas de uma base de dados e de relés de proteção, via protocolo de comunicação IEC 61850 e arquivos de oscilografia. O trabalho aborda o sistema Smart Grid completo incluindo: a aquisição de dados nos relés, detalhando o sistema de comunicação desenvolvido através de um software com um cliente IEC61850 e um servidor OPC e um software com um cliente OPC, que é ativado por eventos configurados para dispará-lo (por exemplo, atuação da proteção); o sistema de pré-tratamento de dados, onde os dados provenientes dos relés e equipamentos de proteção são filtrados, pré-processados e formatados; e o sistema de diagnóstico. Um banco de dados central mantém atualizados os dados de todas essas etapas. O sistema de diagnóstico utiliza algoritmos convencionais e técnicas de inteligência artificial, em particular, um sistema especialista. O sistema especialista foi desenvolvido para lidar com diferentes conjuntos de dados de entrada e com uma possível falta de dados, sempre garantindo a entrega de diagnósticos. Foram realizados testes e simulações para curtos-circuitos (trifásico, dupla-fase, dupla-fase-terra e fase-terra) em alimentadores, transformadores e barras de uma subestação. Esses testes incluíram diferentes estados do sistema de proteção (funcionamento correto e impróprio). O sistema se mostrou totalmente eficaz tanto no caso de disponibilidade completa quanto parcial de informações, sempre fornecendo um diagnóstico do curto-circuito e analisando o funcionamento das funções de proteção da subestação. Dessa forma, possibilita-se uma manutenção muito mais eficiente pelas concessionárias de energia, principalmente no que diz respeito à prevenção de defeitos em equipamentos, rápida resposta a problemas, e necessidade de reparametrização das funções de proteção. O sistema foi instalado com sucesso em uma subestação de distribuição da Companhia Paulista de Força e Luz. / It is important that electrical networks have high levels of reliability in order to maintain the ideal agility and maintenance for better functioning. On the other hand, the often unexpected load growth, failures of protectionrelated equipment and inadequate parameterization of protection functions make the analyses of protection events more complex and time-consuming. Besides, the amount of information that can be retrieved from modern digital relays is constantly increasing. In order to aid a quick decision-making and maintenance practices, this research project aimed to implement a complete diagnosis system that is automatically activated whenever a protection-related event occurs. Information to be analyzed is obtained from a database and from the protection relays, via IEC 61850 communication protocol and oscillography files. The full smart grid system is addressed, including: the data acquisition and communication system developed through a software with an IEC61850 client and an OPC server and another software with an OPC client, which is activated by set triggering events (e.g. protection tripping); the data pre-processing system, in which the data is filtered, preprocessed and formatted; and the diagnostic system. A central database maintains updated all the data. For the diagnostic system, conventional algorithms and artificial intelligence techniques are applied; particularly, an expert system is implemented. The expert system was designed to deal with different sets of input information and uses different techniques to deal with a possible lack of data, always ensuring the delivery of diagnoses. Tests and simulations were performed for short-circuits (three-phase, phase-to-phase, double-phase-to-ground and phase-to-ground) on feeders, transformers and bus bars of a substation. These tests included different states of the protection system (proper functioning and malfunctioning). The diagnostic system proved to be fully effective under both complete and partial availability of information, always providing the fault diagnosis and the analysis of the protection functions. In brief, the system enables a much more efficient maintenance to power distribution utilities, especially when preventing equipment malfunctioning, quick responses towards system problems and the need to re-define some protection functions are required. It was successfully installed in a distribution substation of Companhia Paulista de Força e Luz, a Brazilian power distribution utility.

Neste trabalho foi realizada uma proposta de utilização de Sistemas de Inferência Nebulosos para controlar, em tempo de execução, parâmetros de Algoritmos Genéticos. Esta utilização busca melhorar o desempenho de Algoritmos Genéticos diminuindo, ao mesmo tempo: a média de iterações necessárias para que um Algoritmo Genético encontre o valor ótimo global procurado; bem como diminuindo o número de execuções do mesmo que não são capazes de encontrar o valor ótimo global procurado, nem mesmo para quantidades elevadas de iterações. Para isso, foram analisados os resultados de diversos experimentos com Algoritmos Genéticos, resolvendo instâncias dos problemas de Minimização de Funções e do Caixeiro Viajante, sob diferentes configurações de parâmetros. Com base nos resultados obtidos a partir destes experimentos, foi proposto um modelo com a troca de valores de parâmetros de Algoritmos Genéticos, em tempo de execução, pela utilização de Sistemas de Inferência Nebulosos, de forma a melhorar o desempenho do sistema, minimizando ambas as medidas citadas anteriormente. / This work addressed a proposal of the application of Fuzzy Systems to adjust parameters of Genetic Algorithms, during execution time. This application attempts to improve the performance of Genetic Algorithms by diminishing, at the same time: the average number of necessary generations for a Genetic Algorithm to find the desired global optimum value, as well as diminishing the number of executions of a Genetic Algorithm that are not capable of finding the desired global optimum value even for high numbers of generations. For that purpose, the results of many experiments with Genetic Algorithms were analyzed; addressing instances of the Function Minimization and the Travelling Salesman problems, under different parameter configurations. With the results obtained from these experiments, a model was proposed, for the exchange of parameter values of Genetic Algorithms, in execution time, by using Fuzzy Systems, in order to improve the performance of the system, minimizing both of the measures previously cited.

Neste trabalho foi realizada uma busca por relações, regras e transformações entre duas metodologias constituintes da Inteligência Computacional - a Computação Nebulosa e a Computação Evolutiva. Com a organização e sistematização da existência de tais transformações, obtém-se uma mudança na modelagem de soluções que as utilizam de forma conjunta, possibilitando que teorias e modelos bem estabelecidos em uma das metodologias possam ser aproveitados pela outra de uma forma mais robusta, correta por construção, intrínseca e transparente. Um modelo foi proposto para direcionar o trabalho de pesquisa. Através da análise desse modelo e de uma revisão bibliográfica realizada, transformações pontuais entre as metodologias foram elencadas, e posteriormente consolidadas por meio de experimentos práticos: uma Base de Conhecimento (BC) de um Controlador Lógico Nebuloso foi criada e modificada, conforme a necessidade, através de um Algoritmo Genético (AG). Com a abordagem desenvolvida, além da criação de BCs a partir de pouquíssimo conhecimento sobre o domínio do problema, tornou-se possível a inserção de novos \"comportamentos desejados\" em BCs já existentes, automaticamente, através de AGs. Os resultados desses experimentos, realizados sobre uma plataforma computacional especificada e implementada para este fim, foram apresentados e analisados. / This work addressed a search of relations, rules and transformations between two Computational Intelligence constituent methodologies - Fuzzy Computing and Evolutionary Computing. The existence of these relations changes the actual way of solutions modeling that uses these methodologies, allowing the utilization of well established theories and models of one technique by the other in a more robust, intrinsic and transparent way. Besides the research and systematization of points that indicate the existence of relations between the two methodologies, a model to guide these exploration was proposed. By this model analysis and by the bibliographic revision made, punctual transformations were pointed out, and further consolidated through practical experiments: a Knowledge Base (KB) of a Fuzzy Logic Controller was created and modified automatically by a Genetic Algorithm. With the developed approach, besides the creation of KBs, it became possible to automatically insert new \"desired behaviors\" to existent KBs. The results of such experiments, realized through a computational platform specified and implemented to this task, were presented and analyzed.

Supondo-se que os robôs coexistirão conosco num futuro próximo, é então evidente a necessidade de Arquiteturas de Controle Inteligentes voltadas para a Interação Humano-Robô. Portanto, este trabalho desenvolveu uma Organização de Arquitetura de Controle Inteligente comportamental, cujo objetivo principal é permitir que o robô interaja com as pessoas de maneira intuitiva e que motive a colaboração entre pessoas e robôs. Para isso, um módulo emocional sintético, embasado na teoria bidimensional de emoções, foi integrado para promover a adaptação dos comportamentos do robô, implementados por Esquemas Motores, e a comunicação de seu estado interno de modo inteligível. Esta Organização subsidiou a implantação da Arquitetura de Controle em uma aplicação voltada para a área assistencial da saúde, consistindo, destarte, em um estudo de caso em robótica social assistiva como ferramenta auxiliar para educação especial. Os experimentos realizados demonstraram que a arquitetura de controle desenvolvida é capaz de atender aos requisitos da aplicação, conforme estipulado pelos especialistas consultados. Isto posto, esta tese contribui com o projeto de uma arquitetura de controle capaz de agir mediante a avaliação subjetiva baseada em crenças cognitivas das emoções, o desenvolvimento de um robô móvel de baixo-custo, e a elaboração do estudo de caso em educação especial. / Assuming that robots will coexist with humans in the near future, it is conspicuous the need of Intelligent Control Architectures suitable for Human-Robot Interaction. Henceforth, this research has developed a behavioral Control Architecture Organization, whose main purpose is to allow the intuitive interaction of robot and people, thus fostering the collaboration between them. To this end, a synthetic emotional module, based on the Circumplex emotion theory, promoted the adaptation of the robot behaviors, implemented using Motor Schema theory, and the communication of its internal state. This Organization supported the adoption of the Control Architecture into an assistive application, which consists of the case study of assistive social robots as an auxiliary tool for special education. The experiments have demonstrated that the developed control architecture was able to meet the requirements of the application, which were conceived according to the opinion of the consulted experts. Thereafter, this thesis contributes with the design of a control architecture that is able to act upon the subjective evaluation based on cognitive beliefs of emotions, the development of a low-cost mobile robot, and the development of the case study in special education.

Business intelligence (BI) allows companies to make faster and better-informed decisions. Unfortunately, implementing BI systems in companies in developing countries is minimal. Limited and costly access to the technology, coupled with the cultural background affecting how people perceive BI, has restricted such implementations. The purpose of this phenomenological study was to explore and describe the lived experiences of chief executive officers (CEOs) in northern Mexico to obtain insight into the challenges of implementing BI systems. Research questions focused on the reasons behind the lack of BI systems implementation and the challenges faced by these officers when implementing a new system. This study employed semistructured interviews of 9 CEOs of small- to medium-sized companies. Interview data were coded using open coding techniques to develop themes or patterns, which in turn were aggregated to address the research questions. The lack of implementation was largely attributed to an economic concern among CEOs regarding the final price of implementation. In addition, the lack of systems offerings of localized systems and the working culture of the personnel were significant factors for the lack of investment. These findings may contribute to positive social change by informing managers and officers of companies in Mexico and other developing countries about the challenges and implications in BI implementation. When BI systems can be successfully implemented, both companies and their customers may benefit from improved information processing such as reduced number of errors and faster response times.

In this thesis, research efforts are dedicated towards the development of practical adaptable techniques to be used in Smart Homes and Buildings, with the aim to improve energy management and conservation, while enhancing the learning capabilities of Programmable Communicating Thermostats (PCT) – “transforming” them into smart adaptable devices, i.e., “Smart Thermostats”. An Adaptable Hybrid Intelligent System utilizing Wireless Sensor Network (WSN) and Artificial Intelligence (AI) techniques is presented, based on which, a novel Adaptive Learning System (ALS) model utilizing WSN, a rule-based system and Adaptive Resonance Theory (ART) concepts is proposed. The main goal of the ALS is to adapt to the occupant’s pattern and/or schedule changes by providing comfort, while not ignoring the energy conservation aspect. The proposed ALS analytical model is a technique which enables PCTs to learn and adapt to user input pattern changes and/or other parameters of interest. A new algorithm for finding the global maximum in a predefined interval within a two dimensional space is proposed. The proposed algorithm is a synergy of reward/punish concepts from the reinforcement learning (RL) and agent-based technique, for use in small-scale embedded systems with limited memory and/or processing power, such as the wireless sensor/actuator nodes. An application is implemented to observe the algorithm at work and to demonstrate its main features. It was observed that the “RL and Agent-based Search”, versus the “RL only” technique, yielded better performance results with respect to the number of iterations and function evaluations needed to find the global maximum. Furthermore, a “House Simulator” is developed as a tool to simulate house heating/cooling systems and to assist in the practical implementation of the ALS model under different scenarios. The main building blocks of the simulator are the “House Simulator”, the “Smart Thermostat”, and a placeholder for the “Adaptive Learning Models”. As a result, a novel adaptive learning algorithm, “Observe, Learn and Adapt” (OLA) is proposed and demonstrated, reflecting the main features of the ALS model. Its evaluation is achieved with the aid of the “House Simulator”. OLA, with the use of sensors and the application of the ALS model learning technique, captures the essence of an actual PCT reflecting a smart and adaptable device. The experimental performance results indicate adaptability and potential energy savings of the single in comparison to the zone controlled scenarios with the OLA capabilities being enabled.

In this thesis, research efforts are dedicated towards the development of practical adaptable techniques to be used in Smart Homes and Buildings, with the aim to improve energy management and conservation, while enhancing the learning capabilities of Programmable Communicating Thermostats (PCT) – “transforming” them into smart adaptable devices, i.e., “Smart Thermostats”. An Adaptable Hybrid Intelligent System utilizing Wireless Sensor Network (WSN) and Artificial Intelligence (AI) techniques is presented, based on which, a novel Adaptive Learning System (ALS) model utilizing WSN, a rule-based system and Adaptive Resonance Theory (ART) concepts is proposed. The main goal of the ALS is to adapt to the occupant’s pattern and/or schedule changes by providing comfort, while not ignoring the energy conservation aspect. The proposed ALS analytical model is a technique which enables PCTs to learn and adapt to user input pattern changes and/or other parameters of interest. A new algorithm for finding the global maximum in a predefined interval within a two dimensional space is proposed. The proposed algorithm is a synergy of reward/punish concepts from the reinforcement learning (RL) and agent-based technique, for use in small-scale embedded systems with limited memory and/or processing power, such as the wireless sensor/actuator nodes. An application is implemented to observe the algorithm at work and to demonstrate its main features. It was observed that the “RL and Agent-based Search”, versus the “RL only” technique, yielded better performance results with respect to the number of iterations and function evaluations needed to find the global maximum. Furthermore, a “House Simulator” is developed as a tool to simulate house heating/cooling systems and to assist in the practical implementation of the ALS model under different scenarios. The main building blocks of the simulator are the “House Simulator”, the “Smart Thermostat”, and a placeholder for the “Adaptive Learning Models”. As a result, a novel adaptive learning algorithm, “Observe, Learn and Adapt” (OLA) is proposed and demonstrated, reflecting the main features of the ALS model. Its evaluation is achieved with the aid of the “House Simulator”. OLA, with the use of sensors and the application of the ALS model learning technique, captures the essence of an actual PCT reflecting a smart and adaptable device. The experimental performance results indicate adaptability and potential energy savings of the single in comparison to the zone controlled scenarios with the OLA capabilities being enabled.

Video database applications call for flexible and powerful modeling and querying facilities, which require an integration or interaction between database and knowledge base technologies. It is also necessary for many real life video database applications to incorporate uncertainty, which naturally occurs due to the complex and subjective semantic content of video data. In this thesis study, firstly, a fuzzy conceptual data model is introduced to represent the semantic content of video data. UML (Unified Modeling Language) is utilized and extended to represent uncertain information along with video specific properties at the conceptual level. Secondly, an intelligent fuzzy object-oriented database framework is presented for video database applications. The introduced fuzzy conceptual model is mapped to the presented framework, which is an adaptation of the previously proposed IFOOD architecture. The framework provides modeling and querying of complex and rich semantic content and knowledge of video data including uncertainty. Moreover, it allows (fuzzy) semantic, temporal, (fuzzy) spatial, hierarchical, regional and trajectory queries, based on the video data model. We think that the presented conceptual data model and framework can be adapted to any application domain related to video databases.